13 skills to land an LLM inference engineer role, from quantization to speculative decoding
ashishllm · x · 2026-09-16
ashishllm lists the concepts you need to be hirable as an LLM Inference Engineer: quantization, full/half precision vs int8/int4/NF4, Paged Attention, kernel fusion, Flash Attention, KV Cache, batching, SFT, QLoRA, RLHF, speculative decoding, distillation, and model pruning.
Advanced skill: writing custom CUDA kernels—rare demand but even higher pay, completely optional and usually never required. A handy checklist for inference-role interview prep.
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